Performance of Generalized Spatial Modulation MIMO Over Measured 60GHz Indoor Channels

Abstract

In this paper, we study the capacity and symbol error probability (SEP) of generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) using measured channels that are obtained by channel sounding in an indoor office environment at 60 GHz. Spatial modulation (SM) and GSM are emerging low-complexity MIMO schemes that have been extensively researched for low-GHz (below 6 GHz) communications. Recently, they have been considered and shown to be promising also for millimeter-wave (mmWave) communications. In the simplest possible case, they require only one RF chain both at the transmitter (TX) and receiver (RX), and thus are especially attractive for mmWave communications in which the number of RF chains needs to be as low as possible. Despite of some early works on the theoretical analysis of SM/GSM for mmWave communications, there have been no investigations using realworld channel data. We focus on the office line-of-sight (LOS) scenario and investigate three problems: 1) the performance of GSM using the extracted LOS component of measured channels, 2) the impact of non-LOS (NLOS) components on the performance of GSM, and 3) possible simple modulation and reception algorithms for GSM that rely only on the LOS component of the channel. The results being reported in this paper not only validate the main claims of previous studies based on ideal pure LOS channels but also lead to novel findings. One major conclusion is that NLOS components are harmful to the SEP of GSM and should be avoided. As another important outcome, our results strongly motivate the use of precoding in GSM systems to simultaneously improve the channel capacity and reduce the physical size of MIMO arrays (thus eliminating one major issue of LOS GSM).

Generalized Beamspace Modulation Using Multiplexing: A Breakthrough in mmWave MIMO

“…Complexity and Converge Analysis: The complexity of Algorithm 1 is dominated by the calculation of the gradients in (25) and (28). In each iteration, the calculation of the gradient Algorithm 1 Gradient ascent algorithm to maximize the SE lower bound 1: Initialize p (0) with p i = 1 |F | , i = 1, 2, · · · , |F|, λ (0) with λ ij = 1, j = 1, 2, · · · , N s , the halting criterion and the iteration number k = 0.…”

“…Compute the gradient ∇ λ f (p, λ) by using (28). 8: Carry out the projection to get ∆λ (k+1) by using (34).…”

Single-Carrier Spatial Modulation for the Internet of Things: Design and Performance Evaluation by Using Real Compact and Reconfigurable Antennas

“…Previous studies on transmit spatial modulation are focused on conventional arrays: [6] analyzes solutions based on spatial modulation that exploit the diversity gain of the conventional antenna array and [7]- [14] provide preliminary results on the performance of transmit spatial modulation based on experimental data obtained with conventional antenna arrays. For more information on transmit spatial modulation, please refer to the survey papers [15]- [19].…”

Spatial modulation based on reconfigurable antennas: performance evaluation by using the prototype of a reconfigurable antenna

“…A comprehensive description of the main achievements and latest developments on SM research can be found in [6][7][8][9][10]. Some pioneering and recent experimental activities can be found in [11][12][13][14]. The research literature on *Correspondence: marco.direnzo@l2s.centralesupelec.fr 1 Laboratoire des Signaux et Systèmes, CNRS, CentraleSupelec, Univ Paris-Sud, Université Paris-Saclay, Plateau du Moulon, 91192 Gif-sur-Yvette, France Full list of author information is available at the end of the article SM is vast, and various issues have been tackled during the last few years, which include the analysis of the error probability [15], the design and analysis of transmit-diversity schemes [16,17], and the analysis and optimization of the achievable rate [18,19].…”